Nanos gigantium humeris insidentes!

A Shortest Path Dependency Kernel for Relation Extraction

  • August 23, 2010 8:53 pm

1. Introduction

Information Extraction (IE), which is traditionally divided into three sub-problems:  co-reference resolution, named entity recognition and relation extraction.

In this paper we focus exclusively on extracting relations between predefined types of entities in the ACE corpus.

the use of automatically derived syntactic information can lead to significant improvements in extraction accuracy.

The amount of syntactic knowledge used in IE systems varies from part-of-speech only (Ray and Craven,2001) to chunking (Ray and Craven, 2001) to shallow parse trees(Zelenko et al., 2003) to dependency trees derived from full parse trees ( Culotta and Sorensen, 2004).

The performance however depends not only on the details of the exact models using this information, but also on the details of the exact models using this information.

2. Dependency Graphs

Let e1 and e2 be two entities mentioned in the same sentence such that they are observed to be in a relationship R, i.e R(e1,e2) = 1.

We assume that a relation is to be extracted only between entities mentioned in the same sentence, and that the presence or absence of a relation is independent of the text preceding or following the sentence.

A subset of these word-word dependencies capture the predicate-argument relations present in the sentence. Arguments  are connected to their target predicates either directly through an arc pointing to the predicate, or indirectly through a preposition or infinitive particle.

Word-word dependencies are typically categorized in two classes as follows:

  • Local Dependencies
  • Non-local Dependencies

A context free Grammar parser can be used to extract local dependencies, which for each sentence form a dependency tree. Mildly context sensitive formalisms such as combinatory Categorial Grammar(CCG)(Steedman, 2000) model word-word dependencies more directly and can be used to extract both local and long-distance dependencies, giving rise to a directed acyclic graph.

3 The Shortest Path Hypothesis

contribution of the sentence dependency graph to establishing the relationship R(e1,e2) is almost exclusively concentrated in the shortest path between e1 and e2 in the undirected version of the dependency graph.

If entities e1 and e2 are arguments of the same predicate, then the shortest path between them will pass through the predicate, which may be connected directly to the two entities, or indirectly through prepositions. If e1 and e2 belong to different predicate-argument structures that share a common argument, then the shortest path will pass through this argument.

for the rest, check another paper from the same authors

Print Friendly